By Topic

Fuzzy Clustering of Open-Source Software Quality Data: A Case Study of Mozilla

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Dick, S. ; Univ. of Alberta, Edmonton ; Sadia, A.

We present a fuzzy cluster analysis of software quality data extracted from the Mozilla open-source Web browser. This is a new dataset that combines object-oriented software quality metrics with the number of defects per code unit. We undertake a fuzzy cluster analysis of this dataset, which for the first time addresses the use of both hyperspherical and hyperellipsoidal fuzzy clusters (using the Gath-Geva algorithm) in software quality analysis. Using a Pareto analysis based on the fuzzy clusters, we were able to identify groups of modules having higher defect densities than would be found by merely ranking modules based on any single software metric.

Published in:

Neural Networks, 2006. IJCNN '06. International Joint Conference on

Date of Conference:

0-0 0